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Record W4323351037 · doi:10.1093/jcag/gwac036.043

A43 SEX DIFFERENCES IN THE ASSOCIATION OF HIV WITH METABOLIC DYSFUNCTION-ASSOCIATED FATTY LIVER DISEASE (MAFLD)

2023· article· en· W4323351037 on OpenAlexaff
D Kablawi, Thierry Fosind Tadjo, Jovana Milić, Wesal Elgretli, Claudia Gioè, Bertrand Lebouché, Antonio Cascio, G Guraldo, Giovanni Mazzola, Giada Sebastiani

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2023
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineFatty liverInternal medicineSteatosisGastroenterologyIncidence (geometry)PopulationDiabetes mellitusHepatic fibrosisType 2 diabetesFibrosisDiseaseEndocrinology

Abstract

fetched live from OpenAlex

Abstract Background People with HIV (PWH) are at high risk for metabolic dysfunction-associated fatty liver disease (MAFLD). In the general population, sex differences seem to exist in frequency and severity of MAFLD, with higher prevalence of MAFLD in men, but higher incidence of liver fibrosis in women. Less is known about sex differences in MAFLD and liver fibrosis in the setting of HIV infection. Purpose The aim of this study is to investigate the sex differences in the prevalence of MAFLD in PWH and the severity of liver fibrosis among this population. Method This was a multicenter cohort study including consecutive PWH who underwent screening for MAFLD and liver fibrosis by liver stiffness measurement (LSM) with associated controlled attenuation parameter (CAP). MAFLD was defined as the presence of hepatic steatosis, diagnosed as CAP>270 dB/m, plus any among type 2 diabetes, overweight (BMI>25 Kg/m2) or two other metabolic abnormalities. Significant liver fibrosis was diagnosed as LSM>8 kPa. Incidence of MAFLD and significant liver fibrosis was assessed through survival analysis. Result(s) 1359 PWH (25% females, 30% HCV coinfected) were included. Prevalence of MAFLD at baseline was lower in women than in men with HIV (17.7% vs. 24.3%, p=0.013). Conversely, there was no difference in prevalence of liver fibrosis (10.7% vs. 13.4%). Women with MAFLD were more frequently of black ethnicity (48% vs. 14%, p<0.001), had lower ALT (26.4+20.4 vs. 33.4+22.5; p=0.035), higher HDL cholesterol (1.46+0.57 vs. 1.11+0.33; p<0.001), lower triglycerides (1.69+0.96 vs. 2.47+2.63; p=0.035) compared to men with MAFLD. 485 of these PWH were followed for a median of 3.5 years. Incidence of MAFLD was similar between women and men with HIV. However, incidence of liver fibrosis was higher in women compared to men with HIV (7.0 per 100 person-years [PY] vs. 5.9 per 100 PY; p=0.035) (Figure 1). The higher incidence of significant liver fibrosis occurred particularly after the age of 50 years. On multivariable Cox regression analysis and after adjusting for age, presence of MAFLD (adjusted hazard ratio [aHR] 3.3, 95% CI 2.0-5.6) and female sex (aHR 2.2, 95% CI 1.3-3.5) were independent predictors of developing significant liver fibrosis while CD4 cell count was protective (aHR 0.99, 95% CI 0.99-0.99). Image Conclusion(s) MAFLD seems a sexual dimorphic disease in PWH. Despite having lower rates of MAFLD, women with HIV have higher incidence of significant liver fibrosis compared to men, especially after 50 years of age. Future studies should target adequate consideration of sex differences in clinical investigation of MAFLD to fill current gaps and implement precision medicine for PWH. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest None Declared

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.214
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2023
Admission routes1
Has abstractyes

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